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ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

1. Which ONE of the following statements is a CORRECT adversarial example in the context of machine learning systems that are working on image classifiers.
SELECT ONE OPTION

A) These examples are model specific and are not likely to cause another model trained on same task to fail.
B) Black box attacks based on adversarial examples create an exact duplicate model of the original.
C) These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
D) These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.

2. In a certain coffee producing region of Colombia, there have been some severe weather storms, resulting in massive losses in production. This caused a massive drop in stock price of coffee.
Which ONE of the following types of testing SHOULD be performed for a machine learning model for stock-price prediction to detect influence of such phenomenon as above on price of coffee stock.
SELECT ONE OPTION

A) Testing for bias
B) Testing for security
C) Testing for accuracy
D) Testing for concept drift

3. Max. Score: 2
Al-enabled medical devices are used nowadays for automating certain parts of the medical diagnostic processes. Since these are life-critical process the relevant authorities are considenng bringing about suitable certifications for these Al enabled medical devices. This certification may involve several facets of Al testing (I - V).
I.Autonomy
II.Maintainability
III.Safety
IV.Transparency
V.Side Effects
Which ONE of the following options contains the three MOST required aspects to be satisfied for the above scenario of certification of Al enabled medical devices?
SELECT ONE OPTION

A) Aspects II, III and IV
B) Aspects I, IV, and V
C) Aspects I, II, and III
D) Aspects III, IV, and V

4. Which ONE of the following describes a situation of back-to-back testing the LEAST?
SELECT ONE OPTION

A) Comparison of the results of a current neural network model ML model implemented in platform A (for example Pytorch) with a similar neural network model ML model implemented in platform B (for example Tensorflow), for the same data.
B) Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.
C) Comparison of the results of a home-grown neural network model ML model with results in a neural network model implemented in a standard implementation (for example Pytorch) for same data
D) Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.

Solutions: